1. Field of the Invention
The invention relates to a software-based method and system for forecasting store-level demand for products in a retail environment.
2. Discussion of the Related Art
Today, the static inventory models are based on high-level demographics and do not adjust product assortment by local store demand. Therefore, they are unable to dynamically react to rapidly changing consumer demands. In addition, there is limited capability to understand, on a store-by-store basis, the correlation between consumer demand and weather, local events, pricing, etc. At present, retailers make adjustments to accommodate such demand changes in a reactive mode. There is no existing process in place to proactively account for future causal factors, that will affect sales, or understand at the point of ordering the past consumer trends. This inability to more precisely anticipate future demand perpetuates a pendulum effect at retail, where shelves sway from over-stocked to under-stocked conditions.
For example, today's food retailers are unable to accurately track the profitability of the “fresh” areas of the store. They are suffering from low or no profit margins on areas like the deli, bakery and home meal replacement sections. Critical selling windows are not being calculated and therefore accurate forecasts and preparation quantities do not match with “time of day” buying habits of the consumer. In these areas the ordering, delivery schedules and preparation charts all reside in different locations. There is very little correlation between ingredient ordering, item preparation and the item's critical selling windows.
Accordingly, there is a need in the retail industry for a software system that addresses the problem of effective demand chain management.